Search Results - (( variable detection method algorithm ) OR ( square optimization method algorithm ))
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Modelling of cupping suction system based on system identification method
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Power System State Estimation In Large-Scale Networks
Published 2010“…SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. The Weighted Least Squares (WLS) method is the most popular technique of SE. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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Vibration analysis for early detection of bearing failures
Published 2024“…In summary, the combination of RMS acceleration and kurtosis is proposed as a reliable method for identifying bearing faults.…”
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Final Year Project / Dissertation / Thesis -
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Effect of mixing time and frequency-domain objectives in detecting problematic vibration on unmanned aerial vehicles via barnicle mating optimization
Published 2024“…The goal of this work is to demonstrate the impact of integrating frequency-domain and time-domain analysis as time-domain and frequency-domain objectives. a suggested fitness function that combines the time and frequency domains with a mixing variable. Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and detection time are used to test and assess the fitness function with the Barnicle Mating optimization (BMO) Algorithm optimization technique. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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AI Adoption for Steam Boiler Trip Prevention in Thermal Power Plants
Published 2025“…Furthermore, the hybrid system exhibited a marginal improvement of 0.1% in Root Mean Square error compared to the pure ANN system. These findings collectively emphasize the potential of AI-driven methods in enhancing early detection and prevention of boiler trips, thereby contributing to improved operational safety and efficiency. ?…”
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Modeling of cupping suction system based on system identification method
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Undergraduates Project Papers -
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An application of genetic algorithm and least squares support vector machine for tracing the transmission loss in deregulated power system
Published 2011“…This paper proposes a new method to trace the transmission loss in deregulated power system by applying Genetic Algorithm (GA) and Least Squares Support Vector Machine (LS-SVM). …”
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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Published 2023“…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
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Structural optimization of 4-DOF agricultural robot arm
Published 2024“…This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Hybrid particle swarm optimization algorithm with fine tuning operators
Published 2009“…This method combines the merits of the parameter-free PSO (pf-PSO) and the extrapolated particle swarm optimization like algorithm (ePSO). …”
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A new soft computing model for daily streamflow forecasting
Published 2023“…Climate change; Data streams; Floods; Forecasting; Genetic algorithms; Hydroelectric power plants; Mean square error; Multilayer neural networks; Particle swarm optimization (PSO); Soft computing; Soil conservation; Water conservation; Water management; Water supply; Flow quantification; Multi layer perceptron; Optimization algorithms; Predicting models; Root mean square errors; Soft computing models; Streamflow forecasting; Watershed management; Stream flow; algorithm; forecasting method; hydroelectric power plant; numerical model; optimization; principal component analysis; streamflow; watershed; Helianthus…”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…A coati optimization algorithm is introduced to select input scenarios. …”
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Short term traffic forecasting based on hybrid of firefly algorithm and least squares support vector machine
Published 2015“…The goal of an active traffic management is to manage congestion based on current and predicted traffic conditions.This can be achieved by utilizing traffic historical data to forecast the traffic flow which later supports travellers for a better journey planning.In this study, a new method that integrates Firefly algorithm (FA) with Least Squares Support Vector Machine (LSSVM) is proposed for short term traffic speed forecasting, which is later termed as FA-LSSVM.In particular, the Firefly algorithm which has the advantage in global search is used to optimize the hyper-parameters of LSSVM for efficient data training. …”
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